Ethical Research Practice
As a scientific researcher you must present your work in an unbiased, original and representative manner. Without due care and attention it is easy to drift over the boundaries and into practices that are unacceptable to the scientific community. In this module we will cover three of the main areas that you need to be aware of when communicating your work; plagiarism, image manipulation and reporting negative results/outliers. For each we will show you where the boundaries are and how to stay within them.
Image Manipulation: What's ok, and What's not
Many common types of image manipulation are classified by journals as scientific misconduct. Even if you had no intent to deceive anyone, a finding of misconduct — or even just an accusation — could derail your career.
If your results involve images (such as micrographs, blots, autoradiograms, and photos) then it is vital you learn how to save and process those images without damaging the integrity of the data.
In this session you will learn:
- What practices are considered fraud or misconduct
- How image formats and manipulations affect your data
- How to process images in a way that ensures your science is sound and your results are publishable
Plagiarism: What It Is And How To Avoid It
This session will define plagiarism and present some statistics/facts. Despite the definition being very straightforward, plagiarism is still a huge issue worldwide. Plagiarism can be intentional and unintentional – this is why the key is to inform and educate about what plagiarism actually entails. We will look at examples of plagiarism as well as present a clear strategy to avoid it. We will also cover the notion of self-plagiarism. We will look at some good online plagiarism checkers.
In this session you will learn:
- What plagiarism is and what it’s not
- Some useful (and free) plagiarism checkers
- How to ensure you avoid plagiarism in your work
Reporting Negative Results And Outliers
What is a negative result and when should we report such results? What is the difference between a negative result and an unexpected result? What is an outlier? When is it ok to exclude an outlier, and when should we include outliers in order to report the variation in our experiment?
In this session you will learn:
- What is an outlier?
- When is it ok to exclude an outlier?
- What is a negative result?
- When should we report negative results?